5 research-driven insights for innovative investment strategies

2023 started in the shadow of the Russian invasion of Ukraine, global inflation, and uncertain recession forecasts. It continued with turmoil in the banking system caused by the collapse of Silicon Valley Bank, Signature Bank and the last-minute rescue of Credit Suisse. And more recently, we saw a major escalation in the Israel-Hamas conflict with the October 7 attack and the following military operation. These unpredictable developments have been illustrating in compelling ways the importance of managing risk and catching opportunities as they unfold.

Meanwhile, Language AI has taken the world by storm, with Large Language Models like GPT-4 reshaping how we work, ideate, learn and make decisions.

In this report, we take a look at how the latest innovations in Language AI can offer tangible solutions during volatile and uncertain times, as well as ideas for original investment approaches.

Here are 5 data-driven insights that can help you:

• form a real-time view of economic fundamentals and stay ahead in a world wrestling with inflation, volatility and a possible recession;
• assess unstructured content from multiple sources fast and at scale, and use bearish markets or controversial moments in your favor.

Insight 1

Sentiment-driven Inflation nowcasts strongly enhance cross-asset hedging strategies

Recent research shows that inflation strategies that incorporate sentiment outperform models that depend solely on past observed inflation. RavenPack’s latest white paper proposes a multi-asset allocation strategy for hedging against inflation, which maximizes the portfolio's mean-variance criterion by investing in equities, commodities, and bonds based on inflation nowcasts. Backtested against the US equity market, a 10-year US government bond, and six conventional commodity indexes, the proposed strategy outperformed the S&P 500® in terms of return, volatility, Sharpe ratio, and maximum drawdown.

When targeting volatility levels is		2%	5%	8%
We achieve	Low Realized Volatility Levels	1.9%	4.6%	7.6%
	High Sharpe Ratios	2.40%	1.68%	1.46%
	Annualized Turnover	132%	300%	468%

Insight 2

It is now possible to have a real-time view of GDP evolution with news analytics, even when official data are lagging by months

Advanced language models are now able to “consume“ huge amounts of news and predict GDP in real-time, solving the issue of official data lags. Because they are high-frequency signals, sentiment indicators can even help predict market regime changes, including recessions and recoveries. A recent paper combines macroeconomic variables with real-time sentiment indicators to improve accuracy and timeliness of US GDP nowcasting by up to 70%.

Insight 3

Executives see the economic landscape from within. You can now tap their minds for macro predictions

Earnings calls can offer a window into the views of financial executives on the past, present, and future state of the economy. A real-time C-Level Economic Sentiment Indicator for the US uses NLP event detection and sentiment scoring capabilities to analyze earnings call transcripts. It can indentify significant inflection points in the US economic activity, and detect meaningful changes in the business cycle. The model accurately detects up to 70% of upshifts of the US GDP, and 60% of downshifts.

Insight 4

Sentiment and news analytics provide valuable edges for cross-asset strategy rebalancing, during a challenging time for fixed-income investors

Staying ahead of controversies helps optimize bond selection. Media attention, real-time news, and NLP technology can now help investors outsmart the negative impact of controversies on corporate bonds. Research shows that corporate bonds from issuers involved in severe controversies consistently underperform credit portfolios with low or no controversy bonds.

Bond prices can also be impacted by news related to credit ratings, analyst ratings, and price targets. This paper looks at the impact of credit-related announcements on corporate bond prices using sentiment-based trading strategies that analyze media content. The approach can bring annualized returns amount to 200 bps above the annual credit benchmark at a two-day holding period, and 90 bps at the one-week holding period.

Insight 5

Workforce intelligence emerges as a new source of alpha

Companies hiring for novel tech skills deliver higher investment returns, shows a new research using RavenPack Job Analytics to quantify tech adoption in hiring posts. For instance, a long-only portfolio leveraging the number of novel technology skills detected delivers annualized excess returns of 2.4%, relative to the sector.

Another paper looks at positions, hiring locations and job descriptions, after analyzing over 200 million job postings sourced LinkUp directly from employers websites. Research discovered that monthly hiring growth is indeed positively correlated with future stock performance. What's more, companies with higher hiring growth that also recruit in similar locations month over month, outperform the rest. A long/short sector-neutral portfolio delivers an Information Ratio of 1.1, and Annualized Returns of 2.7% with a weekly holding period.

GOING FURTHER

Shape your data strategy for the unknown

As we navigate the ongoing global economic uncertainty and geopolitical tensions, preparedness remains key.

Our team of data scientists can help address your challenges or offer you inspiration on how to look at data from unprecedented angles. Book a call to explore how data can help you make more informed decisions.